Data Splitting Algorithms for Model Developments

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Documentation for package ‘DSAM’ version 1.0.2

• DESCRIPTION file.
• Package NEWS.

Help Pages

checkFull	Check whether the sample set is full
dataSplit	Main function of data splitting algorithm
DP.initialSample	Initial sampling of DUPLEX
DP.reSample	Repeat sampling of DUPLEX
DSAM_test_largeData	large test dataset
DSAM_test_modData	Moderate test dataset
DSAM_test_smallData	Small test dataset
DUPLEX	'DSAM' - DUPLEX algorithm
getAUC	Get the AUC value between two datasets
getMax	Get the maximum of the output column from the original data set
getMean	Get the mean and standard deviation of the output column from the original data set
getMin	Get the minimum of the output column from the original data set
getSnen	Get sampling number of each SOM neuron
MDUPLEX	'DSAM' - MDUPLEX algorithm
par.default	Default parameter list
remainUnsample	Get the remain unsampled data after 'SSsample'
SBSS.P	'DSAM' - SBSS.P algorithm
selectData	Select specific split data
somCluster	Self-organized map clustering
SOMPLEX	'DSAM' - SOMPLEX algorithm
SS	'DSAM' - SS algorithm
SSsample	Core function of SS sampling
standardise	Standardized data
TIMECON	'DSAM' - Time-consecutive algorithm